Bootstrapping the portmanteau tests in weak auto-regressive moving average models

Ke Zhu ()

MPRA Paper from University Library of Munich, Germany

Abstract: This paper uses a random weighting (RW) method to bootstrap the critical values for the Ljung-Box/Monti portmanteau tests and weighted Ljung-Box/Monti portmanteau tests in weak ARMA models. Unlike the existing methods, no user-chosen parameter is needed to implement the RW method. As an application, these four tests are used to check the model adequacy in power GARCH models. Simulation evidence indicates that the weighted portmanteau tests have the power advantage over other existing tests. A real example on S&P 500 index illustrates the merits of our testing procedure. As one extension work, the block-wise RW method is also studied.

Keywords: Bootstrap method; Portmanteau test; Power GARCH models; Random weighting approach; Weak ARMA models; Weighted portmanteau test. (search for similar items in EconPapers)
JEL-codes: C0 C01 C12 (search for similar items in EconPapers)
Date: 2015-02-06
New Economics Papers: this item is included in nep-ecm and nep-ets
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https://mpra.ub.uni-muenchen.de/61930/1/MPRA_paper_61930.pdf original version (application/pdf)

Related works:
Journal Article: Bootstrapping the portmanteau tests in weak auto-regressive moving average models (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:61930

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